Francesco Ferroni
Principal Scientist at NVIDIA
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolFrancesco Ferroni is a Principal Scientist at NVIDIA with nine years of experience building advanced computer vision and multimodal world models, currently driving the Cosmos video generative model and internet-scale video curation work. He brings a rare blend of deep research (PhD in Computational Physics from Oxford) and hands-on engineering leadership from roles growing Argo AI’s perception teams and shipping production ML systems for autonomous vehicles. His background spans applied research, ML ops, semantic retrieval, and multimodal fusion across text, image, video and 3D, with cross-industry experience from rail startups to large-scale mobility and energy projects. Colleagues know him for translating complex probabilistic modeling and simulation expertise into scalable production pipelines and for starting a rail-tech company with a former collaborator. Located in London, he combines academic rigor, industry-scale deployment experience, and a taste for tackling world-model scale problems that bridge research and product.
9 years of coding experience
10 years of employment as a software developer
PhD Computational Physics, PhD Computational Physics at University of OxfordMEng Mechanical Engineering, MEng Mechanical Engineering at Imperial College LondonInternational Baccalaureate, International Baccalaureate at Impington International Sixth Form
English, Italian, French, Japanese, Portuguese
Github Skills (200)
python10
nearest-neighbors10
feature-engineering10
deep-learning10
cpp10
clustering10
lstm-neural-networks10
rendering10
genetic10
ml10
keras-layer10
neural-network10
computer-vision10
jax10
data-science10
Programming languages (7)
Github contributions (5)
fferroni/PhasedLSTM-Keras
Dec 2016 - Jun 2019
Keras implementation of Phased LSTM [https://arxiv.org/abs/1610.09513]
Contributions:11 commits, 2 PRs, 19 pushes in 2 years 6 months
arxivabslstm-neural-networksdeep-learninglstm
fferroni/GLIP
Nov 2022 - Apr 2023
Grounded Language-Image Pre-training
Contributions:1 review, 3 PRs, 8 pushes in 4 months
pytorchdeep-learningcomputer-visiontrainingpre-training
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